UC Davis

Adaptive Optics (AO) is required to achieve diffraction limited resolution in many real-life imaging applications in biology and medicine. AO is essential to guarantee high fidelity visualization of cellular structures for retinal imaging by correcting ocular aberrations. Aberration correction for mouse retinal imaging by direct wavefront measurement has been demonstrated with great success. However, for mouse eyes, the performance of the wavefront sensor (WFS) based AO can be limited by several factors including non-common path errors, wavefront reconstruction errors, and an ill-defined reference plane. Image-based AO can avoid these issues at the cost of algorithmic execution time. Furthermore, image-based approaches can provide improvements to compactness, accessibility, and even the performance of AO systems. Here, we demonstrate the ability of image-based AO to provide comparable aberration correction and image resolution to the conventional Shack-Hartmann WFS-based AO approach. The residual wavefront error of the mouse eye was monitored during a wavefront sensorless optimization to allow comparison with classical AO. This also allowed us to improve the performance of our AO system for small animal retinal imaging.